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query-inspector is a Claude Code plugin that extracts explicit SQL and infers queries generated by ORM code, then reports potential performance concerns. Its tuning-report skill focuses on findings and suggested fixes; inventory-report builds a catalog of queries. It can run static checks without database access, but inferred SQL is not a guarantee of what an application will execute at runtime.
What query-inspector does
The plugin analyzes query-generating source code and produces reports; it does not edit project files. Its two skills serve different purposes:
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tuning-report: Finds possible concerns such as N+1 patterns, missing index coverage, SQL dialect mismatches, and anti-patterns. Use it to review changed code or run a broader project scan.inventory-report: Catalogs queries, including their bodies and index coverage. Use it when you need an overview rather than prioritized tuning suggestions.
The project describes Kotlin and Java as its primary focus, including JPA/Hibernate, JPA-derived methods, QueryDSL, MyBatis, and native SQL. The creator also lists Kotlin JDSL. Django and SQLAlchemy adapters are available for Python, but the project says those are less thoroughly validated. MySQL and PostgreSQL are named for live-database workflows. See the official query-inspector repository and creator’s launch article for the project’s stated coverage.
How to interpret its findings
The analysis has three possible evidence layers: static heuristics, schema context, and optional live database EXPLAIN. Static analysis is the default and does not require a database. Schema files, entities, migrations, or a live schema can provide context for index-coverage checks; an opt-in EXPLAIN can add query-plan evidence.
#1 Best Overall
Explicit SQL is analyzed as written. For ORM or dynamic queries, the tool infers SQL from source and labels confidence, such as EXACT, INFERRED, or AMBIGUOUS. Dynamic query construction may not be fully reconstructable, so a finding—or the absence of one—does not prove runtime behavior, query speed, or complete query discovery. Check ambiguous or high-impact cases against the SQL actually emitted by the application and its database plan. The repository points to Hibernate SQL logging as one way to verify generated SQL.
Choose a workflow
| Need | Use | Database connection |
|---|---|---|
| Review query-generating changes | tuning-report on Git changes or a range |
Not needed for static analysis |
| Run a one-off tuning pass across the project | tuning-report broader scan option |
Not needed for static analysis |
| Map queries across the project | inventory-report |
Not needed for static analysis |
| Add schema-based index context or plan evidence | Provide schema context, or opt into live EXPLAIN |
Required for live database analysis |
Install and check prerequisites
The repository documents installation through the Claude CLI:
claude plugin marketplace add jogakdal/query-inspector
claude plugin install query-inspector@query-inspector-marketplaceIt also documents a setup script and a skill-copy installation option. Basic use requires Git and Python; the README says the runtime scripts use Python’s standard library. A database connection is not required for basic static analysis. Optional MySQL or PostgreSQL analysis has additional client or driver requirements, and the README lists PyYAML among them. Check the repository’s current instructions before installing, since requirements can change.
Database access is optional, but treat it as a security boundary
The README describes safeguards for live analysis: host patterns containing prod, live, or production are blocked by default, and queries are restricted to SELECT or EXPLAIN. It recommends a host allowlist and a read-only database account, and advises keeping connection URLs in environment variables or .env rather than committed configuration.
These are project-documented controls, not an independent security audit. Before connecting a database, inspect the configuration and safeguards in the exact version you install, and use credentials and network access scoped to the intended environment.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.When it is useful—and what it cannot establish
query-inspector is best treated as a code-review aid that can surface leads before a change ships. Static checks are convenient when database access is unavailable; schema context and live plans can add evidence when you need to investigate further. The report is not a substitute for observing the application’s actual SQL and validating its behavior against the target database.
Rank #4
The reviewed project documentation and launch article do not report a named benchmark, accuracy rate, or time-saved result. The launch article identifies the project as v1.0.0 on October 6, 2026; version availability can change, so consult the repository for the current state. The project identifies its license as MIT, which permits commercial use subject to retaining the license and copyright notice.
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